SLCModeling

This repository archives modeling data for the following Publication:

**Memorization Bias Impacts Modeling of Alternative Conformational States of Solute Carrier Membrane Proteins with Methods from Deep Learning **

G.V.T. Swapna¹, Namita Dube¹, Monica J. Roth², and Gaetano T. Montelione¹

¹Department of Chemistry and Chemical Biology, Center for Biotechnology and Interdisciplinary Studies,
Rensselaer Polytechnic Institute, Troy, NY 12180, USA
²Department of Pharmacology, Robert Wood Johnson Medical School,
Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA

PLOS Computational Biology. accepted 10/6/2025 bioRxiv preprint: https://doi.org/10.1101/2024.07.15.603529

📁 Available Data

Zipped modeling output files are provided for the following proteins:

5OGE, 5I20, 6E9N, 6I1R, 6UKJ, ZnT8, SLC19A1, SLC19A2, SLC35F2

Each protein directory contains outputs from:

Modeller
AlphaFold2
- AF2-flipped-template
- AF2-notemplate
- Flipped-seq
ESMFold

📊 Supplemental Tables

Supplemental Tables 1 and 2 description will go here.

Supplemental Table 1:
Supplemental Table 2:

🧾 Abstract

This study presents a computational pipeline for identifying alternative conformational states of solute carrier (SLC) transporters using deep learning-based structure prediction. We applied AlphaFold2 and ESMFold with custom input modifications (e.g., flipped sequences, altered templates) to explore conformational variability in pseudo-symmetric SLC proteins. This repository provides model outputs and supporting data for independent analysis and reuse.

⚙️ Software Versions

AlphaFold2: v2.3.0 (modified local setup)
Modeller: v10.3
ESMFold: as implemented via Hugging Face/Colab
Python: v3.8+
Other tools: Biopython, TM-score, PyMOL (for post-analysis)

📚 Reference

Swapna GVT, Dube N, Roth MJ, Montelione GT. Modeling Alternative Conformational States of Pseudo-Symmetric Solute Carrier Transporters using Methods from Machine Learning. bioRxiv (2024).
https://doi.org/10.1101/2024.07.15.603529

Swapna GVT, Dube N, Roth MJ, Montelione GT. Memorization Bias Impacts Modeling of Alternative Conformational States of Solute Carrier Membrane Proteins with Methods from Deep Learning. PLOS Comput. Biolog. (2025).

RPIBioinformatics/SLCModeling

About

Topics

Resources

Uh oh!

Stars

Watchers

Forks

Contributors 2

Uh oh!